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Background and Aims: Treatments for cannabis use disorder (CUD) have limited efficacy and little is known about who responds to existing treatments. Accurately predicting who will respond to treatment can improve clinical decision‐making by allowing clinicians to offer the most appropriate level and type of care. This study aimed to determine whether multivariable/machine learning models can be used to classify CUD treatment responders versus non‐responders. Methods: This secondary analysis used data from a National Drug Abuse Treatment Clinical Trials Network multi‐site outpatient clinical trial in the United States. Adults with CUD (n = 302) received 12 weeks of contingency management, brief cessation counseling and were randomized to receive additionally either (1) N‐Acetylcysteine or (2) placebo. Multivariable/machine learning models were used to classify treatment responders (i.e. two consecutive negative urine cannabinoid tests or a 50% reduction in days of use) versus non‐responders using baseline demographic, medical, psychiatric and substance use information. Results: Prediction performance for various machine learning and regression prediction models yielded area under the curves (AUCs) >0.70 for four models (0.72–0.77), with support vector machine models having the highest overall accuracy (73%; 95% CI = 68–78%) and AUC (0.77; 95% CI = 0.72, 0.83). Fourteen variables were retained in at least three of four top models, including demographic (ethnicity, education), medical (diastolic/systolic blood pressure, overall health, neurological diagnosis), psychiatric (depressive symptoms, generalized anxiety disorder, antisocial personality disorder) and substance use (tobacco smoker, baseline cannabinoid level, amphetamine use, age of experimentation with other substances, cannabis withdrawal intensity) characteristics. Conclusions: Multivariable/machine learning models can improve on chance prediction of treatment response to outpatient cannabis use disorder treatment, although further improvements in prediction performance are likely necessary for decisions about clinical care. [ABSTRACT FROM AUTHOR]

Background: Pediatric patients often undergo surgery during terminal admissions. However, the involvement and timing of palliative care consults in caring for these patients has not been readily described. Objective: To describe the presence and timing of palliative care consults for pediatric patients who undergo surgical procedures during terminal admissions. Design: Retrospective cohort study using data from the electronic health record. Setting and Participants: Pediatric patients who underwent at least one surgical procedure during a terminal admission at an urban, quaternary hospital in the United States from January 1, 2016 to December 31, 2021. Main Outcomes and Measures: Patients' medical, surgical, and admission-level characteristics were abstracted. Associations were evaluated between these characteristics and the occurrence and timing of a palliative care consult relative to surgery and death. Results: Of 134 patients, 84% received a palliative care consult during their terminal admission. Approximately 36% of consults occurred before surgery, and 12% were within one day of death. Children without a palliative care consult were more likely than children with a consult to die during surgery (19.1% vs. 2.7%, p = 0.02), have surgery within 24 hours of death (52.4% vs. 15.9%, p < 0.001), and undergo a full resuscitation attempt (47.6% vs. 12.4%, p = 0.002). Receipt of a palliative care consultation did not differ by patient sex, reported race and ethnicity, language, insurance, or income level. Conclusions and Relevance: Palliative care consults support high-quality end-of-life care for children and impact perioperative outcomes, including intensity of surgical care and resuscitation in the final hours of life. [ABSTRACT FROM AUTHOR]

Objective The American College of Rheumatology guidelines for the treatment of lupus nephritis recommend change in induction therapy when response to therapy has not occurred within 6 months. Response is not defined, and renal fibrosis can occur while waiting for this end point. Therefore, a decision support tool to better define response is needed to guide clinicians when starting patients on therapy. This study was undertaken to identify biomarker models with sufficient predictive power to develop such a tool. Methods Urine samples from 140 patients with biopsy-proven lupus nephritis who had not yet started induction therapy were analyzed for a panel of urinary biomarkers. Univariate receiver operating characteristic (ROC) curves were generated for each individual biomarker and compared to the ROC area under the curve values from machine learning models developed using random forest algorithms. Biomarker models of outcome developed with novel markers in addition to clinical markers were compared to those developed with traditional clinical markers alone. Results Models developed with the combined traditional and novel biomarker panels demonstrated clinically meaningful predictive power. Markers most predictive of response were chemokines, cytokines, and markers of cellular damage. Conclusion This is the first study to demonstrate the power of low-abundance biomarker panels and machine learning algorithms for predicting lupus nephritis outcomes. This is a critical first step in research to develop clinically meaningful decision support tools. [ABSTRACT FROM AUTHOR]

Importance: The association between degree of neighborhood deprivation and primary hypertension diagnosis in youth remains understudied., Objective: To assess the association between neighborhood measures of deprivation and primary hypertension diagnosis in youth., Design, Setting, and Participants: This cross-sectional study included 65 452 Delaware Medicaid-insured youths aged 8 to 18 years between January 1, 2014, and December 31, 2019. Residence was geocoded by national area deprivation index (ADI)., Exposures: Higher area deprivation., Main Outcomes and Measures: The main outcome was primary hypertension diagnosis based on International Classification of Diseases, Ninth Revision and Tenth Revision codes. Data were analyzed between September 1, 2021, and December 31, 2022., Results: A total of 65 452 youths were included in the analysis, including 64 307 (98.3%) without a hypertension diagnosis (30 491 [47%] female and 33 813 [53%] male; mean [SD] age, 12.5 (3.1) years; 12 500 [19%] Hispanic, 25 473 [40%] non-Hispanic Black, 24 565 [38%] non-Hispanic White, and 1769 [3%] other race or ethnicity; 13 029 [20%] with obesity; and 31 548 [49%] with an ADI ≥50) and 1145 (1.7%) with a diagnosis of primary hypertension (mean [SD] age, 13.3 [2.8] years; 464 [41%] female and 681 [59%] male; 271 [24%] Hispanic, 460 [40%] non-Hispanic Black, 396 [35%] non-Hispanic White, and 18 [2%] of other race or ethnicity; 705 [62%] with obesity; and 614 [54%] with an ADI ≥50). The mean (SD) duration of full Medicaid benefit coverage was 61 (16) months for those with a diagnosis of primary hypertension and 46.0 (24.3) months for those without. By multivariable logistic regression, residence within communities with ADI greater than or equal to 50 was associated with 60% greater odds of a hypertension diagnosis (odds ratio [OR], 1.61; 95% CI 1.04-2.51). Older age (OR per year, 1.16; 95%, CI, 1.14-1.18), an obesity diagnosis (OR, 5.16; 95% CI, 4.54-5.85), and longer duration of full Medicaid benefit coverage (OR, 1.03; 95% CI, 1.03-1.04) were associated with greater odds of primary hypertension diagnosis, whereas female sex was associated with lower odds (OR, 0.68; 95%, 0.61-0.77). Model fit including a Medicaid-by-ADI interaction term was significant for the interaction and revealed slightly greater odds of hypertension diagnosis for youths with ADI less than 50 (OR, 1.03; 95% CI, 1.03-1.04) vs ADI ≥50 (OR, 1.02; 95% CI, 1.02-1.03). Race and ethnicity were not associated with primary hypertension diagnosis., Conclusions and Relevance: In this cross-sectional study, higher childhood neighborhood ADI, obesity, age, sex, and duration of Medicaid benefit coverage were associated with a primary hypertension diagnosis in youth. Screening algorithms and national guidelines may consider the importance of ADI when assessing for the presence and prevalence of primary hypertension in youth.

This study investigated dental care service utilization among adults with spinal cord injury (SCI) and identified barriers and other factors affecting utilization among this population. There were 192 subjects with SCI who participated in the oral health survey assessing dental care service utilization and they were compared with subjects from the 2004 Behavioral Risk Factors Surveillance System (BRFSS). There was no significant difference in the proportion of subjects with SCI who visited the dentist for any reason in the past year compared to the general population (65.5% vs. 68.8%, p= .350). However, subjects with SCI were less likely to go to the dentist for a dental cleaning in the past year compared to the general population (54.6% vs. 69.4%, p < .001). The three most commonly reported barriers to accessing dental care were cost (40.1%), physical barriers (22.9%), and dental fear (15.1%). Multivariate modeling showed that physical barriers and fear of dental visits were the two significant factors deterring subjects from dental visits in the past year. Physical barriers preventing access to dental facilities and dental fear are prevalent and significantly impede the delivery of dental health care to adults with SCI. Dentists should undertake necessary physical remodeling of their facilities to accommodate wheelchair users and implement appropriate strategies for the management of dental fear among patients with SCI.

The purpose of this study was to determine levels of oral health knowledge and factors associated with adequate oral health knowledge in adults with diabetes. A convenience sample of 253 adult US residents with diabetes completed an oral health survey to assess their knowledge. Results showed that only 47% of the participants answered five or more (out of a maximum of seven) oral health knowledge items related to diabetes correctly. Participants who received oral health information related to diabetes have 2.9 times the odds of possessing adequate oral health knowledge (i.e., answered five or more items correctly) compared to participants who did not received that information controlling for education and race (OR=2.86, 95% CI 1.31-6.24, P=0.008). Given that oral health information provided by health professionals (dental and/or medical) contributes to improve oral health knowledge among adults with diabetes, health professionals should take the opportunity to educate patients with diabetes about the oral manifestations (e.g., dry mouth) and complications (e.g., periodontitis and oral candidiasis) of diabetes and to promote proper oral health behaviors.